AI: What It Is, and Should You Use It
AI: What it is, and should you use it
AI: What it is, and should you use it
In this E-Guide:
The hype surrounding artificial intelligence (AI) and all its potential applications is seemingly unending—but, could it really as powerful as people say it is? AI (artificial intelligence) Keep reading to discover what AI is by definition, why it’s becoming a hot commodity for contact centers, and the pros and cons of implementing it for yourself. 5 trends driving AI in contact centers
The pros and cons of customer service AI
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AI: What it is, and should you use it
AI (artificial intelligence) Margaret Rouse, WhatIs.com
Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of AI (artificial information and rules for using the information), reasoning (using rules to reach approximate intelligence) or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision. 5 trends driving AI in contact centers AI can be categorized as either weak or strong. Weak AI, also known as narrow AI, is an AI system that is designed and trained for a particular task. Virtual personal assistants, such as The pros and cons of Apple's Siri, are a form of weak AI. Strong AI, also known as artificial general intelligence, is customer service AI an AI system with generalized human cognitive abilities. When presented with an unfamiliar task, a strong AI system is able to find a solution without human intervention.
Because hardware, software and staffing costs for AI can be expensive, many vendors are including AI components in their standard offerings, as well as access to Artificial Intelligence as a Service (AIaaS) platforms. AI as a Service allows individuals and companies to experiment with AI for various business purposes and sample multiple platforms before making a commitment. Popular AI cloud offerings include Amazon AI services, IBM Watson Assistant, Microsoft Cognitive Services and Google AI services.
While AI tools present a range of new functionality for businesses ,the use of artificial intelligence raises ethical questions. This is because deep learning algorithms, which underpin many of the most advanced AI tools, are only as smart as the data they are given
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in training. Because a human selects what data should be used for training an AI program, the potential for human bias is inherent and must be monitored closely.
Some industry experts believe that the term artificial intelligence is too closely linked to popular culture, causing the general public to have unrealistic fears about artificial intelligence and improbable expectations about how it will change the workplace and life in AI (artificial general. Researchers and marketers hope the label augmented intelligence, which has a intelligence) more neutral connotation, will help people understand that AI will simply improve products and services, not replace the humans that use them. 5 trends driving AI in contact centers
The pros and cons of customer service AI
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AI: What it is, and should you use it
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AI (artificial intelligence)
5 trends driving AI in contact centers
The pros and cons of customer service AI
Types of artificial intelligence
Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, categorizes AI into four types, from the kind of AI
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systems that exist today to sentient systems, which do not yet exist. His categories are as follows:
• Type 1: Reactive machines. An example is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chess board and make predictions, but it has no memory and cannot use past experiences to AI (artificial inform future ones. It analyzes possible moves -- its own and its opponent -- and intelligence) chooses the most strategic move. Deep Blue and Google's AlphaGO were designed for narrow purposes and cannot easily be applied to another situation. 5 trends driving AI in • Type 2: Limited memory. These AI systems can use past experiences to inform future decisions. Some of the decision-making functions in self-driving cars are contact centers designed this way. Observations inform actions happening in the not-so-distant future, such as a car changing lanes. These observations are not stored permanently. The pros and cons of • Type 3: Theory of mind. This psychology term refers to the understanding that customer service AI others have their own beliefs, desires and intentions that impact the decisions they make. This kind of AI does not yet exist. • Type 4: Self-awareness. In this category, AI systems have a sense of self, have consciousness. Machines with self-awareness understand their current state and can use the information to infer what others are feeling. This type of AI does not yet exist .
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AI (artificial intelligence)
5 trends driving AI in contact centers
The pros and cons of customer service AI
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Examples of AI technology
AI is incorporated into a variety of different types of technology. Here are seven examples.
• Automation: What makes a system or process function automatically. For example, robotic process automation (RPA) can be programmed to perform high-volume, AI (artificial repeatable tasks that humans normally performed. RPA is different from IT intelligence) automation in that it can adapt to changing circumstances. • Machine learning: The science of getting a computer to act without programming . 5 trends driving AI in Deep learning is a subset of machine learning that, in very simple terms, can be contact centers thought of as the automation of predictive analytics. There are three types of machine learning algorithms: The pros and cons of o Supervised learning: Data sets are labeled so that patterns can be detected and used to label new data sets customer service AI o Unsupervised learning: Data sets aren't labeled and are sorted according to similarities or differences o Reinforcement learning: Data sets aren't labeled but, after performing an action or several actions, the AI system is given feedback • Machine vision: The science of allowing computers to see. This technology captures and analyzes visual information using a camera, analog-to-digital conversion and digital signal processing. It is often compared to human eyesight, but machine vision isn't bound by biology and can be programmed to see through walls, for example. It is used in a range of applications from signature identification to medical image analysis. Computer vision, which is focused on machine-based image processing, is often conflated with machine vision. • Natural language processing (NLP): The processing of human -- and not computer -- language by a computer program. One of the older and best known examples of NLP is spam detection, which looks at the subject line and the text of an email and
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decides if it's junk. Current approaches to NLP are based on machine learning. NLP tasks include text translation, sentiment analysis and speech recognition. • Robotics: A field of engineering focused on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. They are used in assembly lines for car production or by NASA to move large objects in space. Researchers are also using machine learning to build AI (artificial robots that can interact in social settings. • Self-driving cars: These use a combination of computer vision, image recognition intelligence) and deep learning to build automated skill at piloting a vehicle while staying in a given lane and avoiding unexpected obstructions, such as pedestrians. 5 trends driving AI in contact centers AI applications The pros and cons of Artificial intelligence has made its way into a number of areas. Here are six examples. customer service AI • AI in healthcare. The biggest bets are on improving patient outcomes and reducing costs. Companies are applying machine learning to make better and faster diagnoses than humans. One of the best known healthcare technologies is IBM Watson. It understands natural language and is capable of responding to questions asked of it. The system mines patient data and other available data sources to form a hypothesis, which it then presents with a confidence scoring schema. Other AI applications include chatbots, a computer program used online to answer questions and assist customers, to help schedule follow-up appointments or aid patients through the billing process, and virtual health assistants that provide basic medical feedback. • AI in business. Robotic process automation is being applied to highly repetitive tasks normally performed by humans. Machine learning algorithms are being integrated into analytics and CRM platforms to uncover information on how to better serve customers. Chatbots have been incorporated into websites to provide
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immediate service to customers. Automation of job positions has also become a talking point among academics and IT analysts. • AI in education. AI can automate grading, giving educators more time. AI can assess students and adapt to their needs, helping them work at their own pace. AI tutors can provide additional support to students, ensuring they stay on track. AI could change where and how students learn, perhaps even replacing some teachers. AI (artificial • AI in finance. AI in personal finance applications, such as Mint or Turbo Tax, is disrupting financial institutions. Applications such as these collect personal data and intelligence) provide financial advice. Other programs, such as IBM Watson, have been applied to the process of buying a home. Today, software performs much of the trading on 5 trends driving AI in Wall Street. contact centers • AI in law. The discovery process, sifting through of documents, in law is often overwhelming for humans. Automating this process is a more efficient use of time. The pros and cons of Startups are also building question-and-answer computer assistants that can sift programmed-to-answer questions by examining the taxonomy and ontology customer service AI associated with a database. • AI in manufacturing. This is an area that has been at the forefront of incorporating robots into the workflow. Industrial robots used to perform single tasks and were separated from human workers, but as the technology advanced that changed .
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AI (artificial intelligence)
5 trends driving AI in contact centers
The pros and cons of customer service AI Security and ethical concerns
The application of AI in the realm of self-driving cars raises security as well as ethical concerns. Cars can be hacked, and when an autonomous vehicle is involved in an accident, liability is unclear. Autonomous vehicles may also be put in a position where an accident is unavoidable, forcing the programming to make an ethical decision about how to minimize damage.
Another major concern is the potential for abuse of AI tools. Hackers are starting to use sophisticated machine learning tools to gain access to sensitive systems, complicating the issue of security beyond its current state.
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Deep learning-based video and audio generation tools also present bad actors with the tools necessary to create so-called deepfakes , convincingly fabricated videos of public figures saying or doing things that never took place .
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AI (artificial intelligence)
5 trends driving AI in contact centers
The pros and cons of customer service AI
Regulation of AI technology
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Despite these potential risks, there are few regulations governing the use AI tools, and where laws do exist, the typically pertain to AI only indirectly. For example, federal Fair Lending regulations require financial institutions to explain credit decisions to potential customers, which limit the extent to which lenders can use deep learning algorithms, which by their nature are typically opaque. Europe's GDPR puts strict limits on how enterprises can use consumer data, which impedes the training and functionality of many consumer- AI (artificial facing AI applications. intelligence) In 2016, the National Science and Technology Council issued a report examining the 5 trends driving AI in potential role governmental regulation might play in AI development, but it did not contact centers recommend specific legislation be considered. Since that time the issue has received little attention from lawmakers. The pros and cons of customer service AI
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5 trends driving AI in contact centers Micah Levine, Associate Site Editor AI (artificial intelligence) Contact center vendors across the market are introducing AI as a feature of their platforms. From chatbots to predictive analytics to interactive voice response, the possibilities appear 5 trends driving AI in endless. With the abundance of AI in the contact center, one has to wonder, is the contact centers technology actually solving the concerns of customers and agents? "Sometimes customers want something very straightforward that doesn't even need AI. The pros and cons of Others want the full power AI brings," said Jafar Adibi, head of data science and AI at customer service AI Talkdesk. "A good AI system makes three things possible: gathering data, providing context and inferencing."
With every vendor claiming to offer AI in the contact center, it can be difficult to separate true innovative AI features, like voice fraud detection, from AI as a buzzword. According to Adibi, vendors are focusing on five trends to drive adoption of contact center AI.
1. Optimization. Vendors are using AI to streamline the contact center experience. AI can collect information, provide context for interactions, and ensure a faster call time and a better customer experience by allowing agents to get directly to the call's purpose.
"If a flight is canceled, for example, and a customer calls the airline contact center, AI can provide context taken from the flight number and give the agent information, such as that the flight was canceled, where the flight was headed and when the next available flights
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are," Adibi said. "All of this is done without the customer having to provide additional information during the interaction."
Contact centers can also use the context provided by AI to route calls to the agent with the appropriate skills to quickly resolve an issue.
AI (artificial 2. Automation. Automation plays a vital role in both customer experience and agent intelligence) retention. Automation through chatbots has seen a surge in popularity due to the changing demographics of contact center customers. According to Adibi, millennials are more likely to 5 trends driving AI in choose text-based communication, so having sophisticated chatbot AI is essential to their contact centers customer experience. By automating with AI chatbots, more issues can be solved without the aid of an agent. The pros and cons of In the case of a canceled flight, a chatbot might be able to use the customer's flight number customer service AI to automatically offer new flight suggestions and make it easier for the customer to reschedule.
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Likewise, AI being able to autofill forms post-call is another way to lessen the workload placed on A good AI system makes agents. Adibi said automating workflows leads three things possible: to happier agents who stay longer in their gathering data, positions. providing context and AI (artificial 3. Prediction. AI in contact centers is often inferencing. intelligence) focused on predictive behavior, such as analyzing data sets to estimate how many calls head of data science and 5 trends driving AI in are expected in an upcoming shift to dictate contact centers how agents need to be scheduled. Vendors are AI, Talkdesk taking the technology a step further by The pros and cons of developing predictive analytics that can tell Jafar Adibi customer service AI agents what the calls will be about.
For example, if a company has a new product launch, the AI could predict what customer calls will be related to the new product and agents can adjust their interactions accordingly.
4. Recommendations. AI can also be used to manage agent performance by monitoring agents during a customer interaction and making recommendations. Using voice analysis, for example, AI can recognize indicators that a customer is stressed and provide recommendations to the agent in real time to assist in handling the call.
Some AI in contact centers can go as far as recommending that agents go grab a coffee if it recognizes a dip in efficiency or performance. Vendors are particularly interested in AI recommendations, as they can directly affect the customer experience.
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5. Discovery. One of the more useful trends in AI in the contact center is AI-enabled discovery and analytics. Contact centers can find value in AI that can comb through call data and determine how effective an interaction was and how the interaction could be replicated across the contact center.
Discovery AI in contact centers offers the ability to recognize patterns and locate any AI (artificial fraudulent activity. AI that discovers and analyzes patterns, whether in customer behavior or intelligence) agent responsiveness, can be used to implement new tactics and practices across organizations, which Adibi said can lead to a better customer experience. 5 trends driving AI in contact centers
The pros and cons of customer service AI
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The pros and cons of customer service AI Scott Robinson, Director of business intelligence AI (artificial intelligence) More and more, chatbots are being used as service desk utilities, replacing human support personnel. This is visible in the marketplace, as many support pages on commercial 5 trends driving AI in websites provide bot assistance and the industry integrates more self-service platform contact centers technology. Consumers frequently are put off by efforts to obtain support over the phone, only to The pros and cons of become lost in an endless interactive voice response phone maze asking them to "press customer service AI this button" and "listen to these options," when all they want is a human. While automation often saves money for the enterprise, there remains a question of whether customer service AI is positive for the customer. An indispensable human touch?
For some, chatbots are a step in the wrong direction -- a move away from human empathy and compassion that keep customers loyal even when things have gone south.
For instance, in a survey of 1,000 customers and service professionals, Cogito Corp. found that 80% of those responding said a personalized experience is crucial, and 97% considered it important that customer service take an authentic interest in solving their problem.
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The survey concludes that better conversations lead to greater customer satisfaction and loyalty, and a competitive advantage.
However, vendors of chatbot platforms are incorporating personalization features into their bots to address this deficit. Salesforce, in particular, with its new Einstein Bots, is able to connect a service bot to customer profile data, giving the bot access to the customer's AI (artificial purchase and service histories, as well as enabling it to register customer sentiment to aid in intelligence) fine-tuning its responses.
5 trends driving AI in Those capabilities aren't yet common among chatbots, but may soon be -- after all, it's contact centers already routine for CRM service software to put customer profile and service history data at the fingertips of human service personnel. The pros and cons of But is that enough? To remain loyal to the brand, the customer seeking help needs that help customer service AI to be more than just knowledgeable -- they need for it to be sympathetic.
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AI (artificial intelligence)
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AI can make a chatbot seem more human
The question of whether the customer wants to chat with another human or a bot is by no means settled. Opinions abound: A PwC study said customers want more humanity and less automation, especially when something goes wrong." And in the U.K., a MyClever AI (artificial customer survey rated human service over bot service, with the complaints that bots often intelligence) have trouble with even simple answers and fail to meet expectations in friendliness. 5 trends driving AI in On the other hand, a 2017 report from the For some, chatbots are a contact centers International Customer Management Institute step in the wrong showed that 85% of survey respondents said The pros and cons of direction -- a move away they want to see their organization adopt or customer service AI expand the use of AI. Moreover, in the 2018 from the empathy and State of Chatbots report -- a joint effort between compassion that keep Drift, SurveyMonkey Audience, Salesforce and customers loyal even MyClever -- 69% of consumers said they prefer chatbots for quick communication with a when things have gone company. south.
Can AI help the bot take that final step, combining availability and speed with a humanlike touch?
The answer to that is yes, with qualifications. Bots must have a clear set of rules about when to elevate service to a human, and be given real-time sentiment analysis tools: With this emerging technology, chatbots' actions can be cued by a customer's anger, stress or
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confusion to shift conversational styles -- from cool and technical to warm and friendly, from humorous to snarky -- depending on what will set the customer at ease.
Most chatbot platforms now enable flexibility in configuring highly variable response styles, and for the most part, programming skills are not required. The sentiment analysis piece is not so easy: It's a third-party component, making compatibility a consideration. AI (artificial intelligence) There's no turning back. Customer service AI is here to stay -- and it is rapidly becoming the default. 5 trends driving AI in contact centers
The pros and cons of customer service AI
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